Signal processing system for tonal noise robustness

1. A signal pre-processing method comprising:

obtaining an input signal comprising a tonal noise peak;

smoothing the input signal in a frequency-based direction to attenuate the tonal noise peak in the input signal and obtain a smoothed signal, where smoothing the input signal comprises:

determining a first windowed average of the input signal to obtain a first averaged signal;

determining a second windowed average of the first averaged signal by selecting a window of signal components starting at an index point in the first averaged signal;

comparing at least one of the signal components to the first windowed average of the input signal at the index point to identify an outlying signal component that exceeds the first windowed average of the input signal at the index point; and

excluding the outlying signal component in determining the second windowed average;

obtaining a background noise estimate; and

blending the smoothed signal with the input signal based on the background noise estimate to obtain an output signal, where blending comprises:

outputting the input signal as the output signal in response to a determination that the background noise estimate satisfies a first predetermined condition; and

outputting the smoothed signal as the output signal in response to a determination that the background noise estimate satisfies a second predetermined condition different than the first predetermined condition.

2. The method of claim 1 , where:

smoothing the input signal comprises attenuating tonal noise in the input signal.

3. The method of claim 2 , where:

obtaining the input signal comprises obtaining an input signal comprising tonal noise and desired signal peaks; and

where smoothing the input signal further comprises attenuating the desired signal peaks to obtain the smoothed signal.

4. The method of claim 1 , where blending comprises forming a signal-to-noise ratio weighted mix of the input signal and the smoothed signal.

5. A signal processing system comprising:

a memory comprising:

a smoothing program which smoothes an input signal in a frequency-based direction by applying an attenuation to a tonal noise peak in the input signal to obtain a smoothed signal, where the attenuation comprises a windowed average of the input signal, where the smoothing program compares signal components of the input signal to a magnitude threshold to identify an outlying signal component that exceeds the magnitude threshold, and where the smoothing program excludes the outlying signal component in determining the windowed average;

a background noise estimate; and

a blending program which combines the smoothed signal with the input signal based on the background noise estimate to produce an output signal, where the blending program comprises a first blending rule configured to output the input signal as the output signal in response to a determination that the background noise estimate satisfies a first predetermined condition; and where the blending program comprises a second blending rule configured to output the smoothed signal as the output signal in response to a determination that the background noise estimate satisfies a second predetermined condition different than the first predetermined condition; and

a processor coupled to the memory which executes the smoothing program and blending program.

6. The system of claim 3 , where the attenuation comprises a two-pass windowed average of the input signal.

7. The system of claim 5 , where the attenuation comprises a two-pass windowed average of the input signal, excluding outlying signal components during a second pass of the two-pass windowed average.

8. The system of claim 5 , where the blending program implements the first blending rule when a signal-to-noise estimate based on the background noise estimate is greater than an upper threshold.

9. The system of claim 5 , where the blending program implements the second blending rule when a signal-to-noise estimate based on the background noise estimate is less than a lower threshold.

10. The system of claim 5 , where the blending program comprises a third blending rule configured to set the output signal by applying a blending function of the input signal and the smoothed signal, when a signal-to-noise estimate based on the background noise estimate falls between an upper SNR threshold and a lower SNR threshold.

11. The system of claim 10 , where the blending function comprises a linear weighted average of the input signal and the smoothed signal.

12. A signal pre-processing system comprising:

a memory comprising:

an input signal representation comprising tonal noise peaks and desired signal peaks;

a background noise estimate;

a signal-to-noise ratio (SNR) estimate based on the input signal representation and the background noise estimate;

a multi-pass windowing program operable to successively apply averaging windows to the input signal representation to smooth the input signal representation in a frequency-based direction to attenuate the tonal noise peaks and the desired signal peaks and obtain a smoothed signal representation;

an upper SNR threshold;

a lower SNR threshold;

a blending program for generating an output signal component from an input signal component of the input signal representation and a smoothed signal component of the smoothed signal representation, the blending program implementing at least the following blending rules:

set the output signal component to the input signal component, when the SNR estimate is greater than the upper SNR threshold;

set the output signal component to the smoothed signal component, when the SNR estimate is less than the lower SNR threshold; and

set the output signal component by applying a blending function of the input signal component and the smoothed signal component, when the SNR estimate falls between the upper SNR threshold and the lower SNR threshold; and

a processor coupled to the memory which executes the multi-pass windowing program and the blending program.

13. The system of claim 12 , where the averaging windows comprise a first length averaging window and a different second length averaging window.

14. The system of claim 13 , where the different second length averaging window is longer than the first length averaging window, and where the multi-pass windowing program excludes an outlying signal component during application of the longer second length averaging window.

15. The system of claim 14 , where the outlying signal component exceeds an averaged signal level obtained through application of the first length averaging window.

16. The system of claim 12 , where the blending function is a linearly dependent mix of the smoothed signal component and the input signal component.

17. The system of claim 13 , where the different second length averaging window is shorter than the first length averaging window.

18. A product comprising: a non-transitory machine readable medium

a machine readable medium; and

instructions stored on the medium that cause a processing system to:

obtain a background noise estimate;

smooth an input signal in a frequency-based direction to attenuate tonal noise peaks in the input signal to obtain a smoothed signal, where the instructions which attenuate tonal noise peaks comprise instructions that cause the processing system to:

determine a first windowed average of the input signal to obtain a first averaged signal;

determine a second windowed average of the first averaged signal by selecting a window of signal components starting at an index point in the first averaged signal;

compare at least one of the signal components to the first windowed average of the input signal at the index point to identify an outlying signal component that exceeds the first windowed average of the input signal at the index point; and

exclude the outlying signal component in determining the second windowed average; and

apply blending rules to combine the smoothed signal with the input signal, based on the background noise estimate, to form an output signal, where the blending rules comprise a first blending rule configured to output the input signal as the output signal in response to a determination that the background noise estimate satisfies a first predetermined condition; and where the blending rules comprise a second blending rule configured to output the smoothed signal as the output signal in response to a determination that the background noise estimate satisfies a second predetermined condition different than the first predetermined condition.

19. The product of claim 18 , where the instructions which attenuate the peaks comprise:

instructions which attenuate tonal noise peaks and desired signal peaks.

20. The product of claim 18 , where the instructions which attenuate peaks comprise:

windowed averaging instructions.

21. The product of claim 18 , where the instructions which attenuate peaks comprise:

multiple-pass windowed averaging instructions.

22. The product of claim 18 , where the instructions which attenuate peaks comprise:

multiple-pass windowed averaging instructions which discard outlying signal components.

23. The product of claim 22 , where the outlying signal samples comprise tonal noise peak components and desired signal peak components.

24. The product of claim 18 , where the instructions which apply the blending rules comprise:

instructions which form a signal-to-noise ratio weighted mix of the input signal and the smoothed signal.

25. The product of claim 24 , where the medium further comprises instructions which determine a signal-to-noise (SNR) measure based on the background noise estimate and the input signal, and where the weighted mix comprises:

y =(1−(SNR/(upper−lower)))* s +(SNR/(upper−lower))* x , where:

‘y’ is an output signal component, ‘s’ is a smoothed signal component, ‘x’ is an input signal component, ‘upper’ is an upper SNR threshold, ‘lower’ is a lower SNR threshold, and ‘SNR’ is the SNR measure.

26. The method of claim 1 , where blending comprises mixing the smoothed signal with the input signal by a processor configured to generate the output signal with one or more first portions set to the input signal or an average of the input signal and the smoothed signal, and one or more second portions set to the smoothed signal or an average of the input signal and the smoothed signal.

27. The system of claim 12 , where the output signal comprises one or more first portions set to the input signal or an average of the input signal and the smoothed signal, and one or more second portions set to the smoothed signal or an average of the input signal and the smoothed signal.

28. The method of claim 1 , where smoothing the input signal comprises smoothing the input signal by a processor configured to execute a smoothing program stored in a non-transitory computer-readable medium.

29. The method of claim 1 , where the determination that the background noise estimate satisfies the first predetermined condition comprises a determination that a signal-to-noise estimate based on the background noise estimate is greater than an upper SNR threshold;

where the determination that the background noise estimate satisfies the second predetermined condition comprises a determination that a signal-to-noise estimate based on the background noise estimate is less than a lower SNR threshold; and

where blending the smoothed signal with the input signal further comprises:

setting the output signal by applying a blending function of the input signal and the smoothed signal, when a signal-to-noise estimate falls between the upper SNR threshold and the lower SNR threshold.

30. The system of claim 5 , where the smoothing program determines a first windowed average of the input signal to obtain a first averaged signal, where the smoothing program determines a second windowed average of the first averaged signal by selecting a window of signal components starting at an index point in the first averaged signal, where the smoothing program compares at least one of the signal components to the first windowed average of the input signal at the index point to identify an outlying signal component that exceeds the first windowed average of the input signal at the index point, where the smoothing program excludes the outlying signal component in determining the second windowed average, and where the blending program uses the second windowed average as the smoothed signal.

31. The system of claim 12 , where the smoothed signal representation comprises a multi-pass windowed average of the input signal representation, where the multi-pass windowing program compares signal components of the input signal to a magnitude threshold to identify an outlying signal component that exceeds the magnitude threshold, and where the multi-pass windowing program excludes the outlying signal component in determining the multi-pass windowed average.

32. The system of claim 12 , where the multi-pass windowing program determines a first windowed average of the input signal representation to obtain a first averaged signal, where the multi-pass windowing program determines a second windowed average of the first averaged signal by selecting a window of signal components starting at an index point in the first averaged signal, where the multi-pass windowing program compares at least one of the signal components to the first windowed average of the input signal at the index point to identify an outlying signal component that exceeds the first windowed average of the input signal at the index point, where the multi-pass windowing program excludes the outlying signal component in determining the second windowed average, and where the blending program uses the second windowed average as the smoothed signal representation.